Estimating vehicle CO₂ emissions from rated specifications

Version: 2026-09-21

The prepared dataset contains 7,385 vehicle-rating records. Inputs include make, model, vehicle class, engine characteristics and fuel consumption. Categorical expansion produces 2,127 input features. Fuel consumption and CO₂ ratings are closely linked; the result is a rating-data estimator rather than an independent measurement of road emissions.

Related vehicle variants may cross the row-based split. Hold out model families and model years to test transfer. Do not interpret directional curves as causal effects, or vary city consumption while assuming every correlated specification can remain physically unchanged. Road conditions and driving behaviour are outside this dataset.

Open the .nd project in Neural Designer. Its embedded data, parameters, saved sample roles and task report are preserved. If the original CSV path is unavailable, select the CSV included here. The source CSV may include unused columns; the embedded project defines the exact modelling schema.

The charts/ directory contains standalone HTML exported with the application chart builder. The schema and test-metrics files identify the exact inputs, outputs, evidence and source hash.

Dataset source: https://open.canada.ca/data/en/dataset/98f1a129-f628-4ce4-b24d-6f16bf24dd64
Retain the source attribution and its applicable dataset terms.

The original HTML expression is included unchanged. native-model.js contains the same mathematical functions extracted from it.
